Optimizing Design of Stand-alone Hybrid Solar Micro-CHP ‎Systems Using LUS Based Particle Swarm Optimization ‎Algorithm ‎

Utilizing the combined cooling, heating and power generation (CHP) systems to produce cooling, heat and electricity is growing rapidly due to their high efficiency and low emissions in commercial and industrial applications. In conventional CHP systems the deficit of the system power can be purchased from the grid. However, this system cannot be used as the standalone application. The hybrid solar micro-CHP system can be worked as a standalone system for remote areas and other places which the access to grid is hard and costly. In this paper, by using energy and economic analyses, the type and the number of the required microturbines for the specific electricity and heat load curves during a year are selected. For performing this task, maximizing the actual annual benefit of the system is considered as objective function. Then, particle swarm optimization (PSO) algorithm and local unimodal sampling (LUS) technique is developed to calculate the type and number of prime mover and also the area of photovoltaic panels.